Machine Learning Engineer
2021 - PRESENTBlackRock- Developed and productionized machine learning models to predict financial instrument prices using Scikit-learn, PyTorch, NumPy, Pandas, Python, Docker, and AWS.
- Managed stakeholder relationships by scoping project requirements, designing key success metrics, specifying timelines, and presenting findings.
- Led the introduction of Agile processes for new and existing machine learning projects.
- Presented model designs and results to technical and non-technical stakeholders.
- Engineered a model backtesting and monitoring framework using Python, Docker, and AWS—EC2, SageMaker, and CloudWatch.
Technologies: Amazon Web Services (AWS), Artificial Intelligence (AI), Data Science, Python, PyTorch, NumPy, Pandas, Docker, Scikit-learnMachine Learning Engineer
2019 - 2021Getaroom- Improved and productized a deep learning NLP model—achieving a classification accuracy of over 95%.
- Designed and implemented new models for predicting sales of new properties, therefore making property price collection more accurate and efficient.
- Performed an analysis on large, noisy datasets before presenting the findings to nontechnical teams.
- Increased the performance of existing machine learning models through parallelization, the user of GPUs, and refactoring of Python code.
- Ensured AI/ML solutions are explainable to nontechnical members of staff.
- Wrote efficient Athena queries on large, noisy datasets for data analysis and development.
Technologies: Amazon Web Services (AWS), AWS CLI, AWS Glue, Amazon SageMaker, Amazon Athena, Amazon S3 (AWS S3), Kubernetes, Terraform, Keras, NumPy, TensorFlow, PythonSoftware Developer
2017 - 2019Barrachd- Developed an online app using Python (NumPy, SciPy), C# .NET, JavaScript, React, and SQL.
- Led the design and implementation of a microservice that matched large volumes of incoming messages to complex queries. Using advanced Python and linear algebra, this service decreased processing time from minutes to less than one second.
- Participated in the design and implementation of a component that clustered large volumes of incoming messages, therefore streamlining the data processing pipeline.
- Worked in a team to implement data analytics software that allowed users to visualize and analyze data from millions of social media interactions every hour. This allowed clients to gain actionable insights from large volumes of unorganized data.
- Developed integrations with a large number of social media APIs, ensuring minimal data was collected to keep operational costs low and ensure clients only saw relevant information.
- Presented and described technically complex components to technical and nontechnical members of the team.
Technologies: SQL, React, JavaScript, C#.NET, SciPy, NumPy, PythonQA Lead | Software Developer
2014 - 2017RotaGeek- Initiated and led the entire testing process leading to fewer bugs, a more robust product, and a faster development cycle.
- Chose the software release dates, balancing customer requirements with product quality.
- Gathered feedback from clients to align future product developments with client needs.
- Communicated and demonstrated the product to technical and non-technical stakeholders.
Technologies: Selenium, Python, HTML, SQL, JavaScript, C#.NET
Thomas James Cartwright
Machine Learning Engineer and Developer in Edinburgh, United Kingdom
Member since July 17, 2020
Thomas has three years of industry experience designing, developing and productionising machine learning solutions and five years of industry experience developing software solutions. He holds a Master of Science in AI (with merit) from the University of Edinburgh, specialising in traditional machine learning, deep learning, and reinforcement learning. Due to a keen interest in entrepreneurship, Thomas joined Toptal to contribute his expertise and explore new challenges.
Thomas is now available for hire
Experience
- Python 8 years
- Machine Learning 4 years
- Data Science 4 years
- Deep Neural Networks 3 years
- Artificial Intelligence (AI) 3 years
- Recommendation Systems 2 years
- Amazon Web Services (AWS) 1 year
- Reinforcement Learning 1 year
Availability
Part-time
Preferred Environment
Artificial Intelligence (AI), Machine Learning, Data Science
The most amazing...
...thing I have developed is a machine learning agent that taught a simulated robot to walk.
Employment
Experience
- Recommendation System for Citizen Sciencehttps://github.com/tjcdev/qc-recommender
A system that recommends new SciStarter projects to users on the Citizen Science web portal. The recommender system uses the user's previously completed projects, and the contents of projects, to build a profile of users interests.
The unsupervised task clustering and user recommendation system on the SciStarter website was used to increase engagement and the quality of user task completion.
Skills
Languages
Python, SQL, C#Libraries/APIs
Pandas, NumPy, TensorFlow, PyTorch, Scikit-learn, KerasOther
Recommendation Systems, Machine Learning, Artificial Intelligence (AI), Data Engineering, Deep Neural Networks, Natural Language Processing (NLP), Reinforcement LearningParadigms
Data SciencePlatforms
Amazon Web Services (AWS), DockerStorage
Google Cloud
Education
- Master's Degree in Artificial Intelligence2017 - 2019University of Edinburgh - Edinburgh, Scotland
- Bachelor's Degree in Mathematics2010 - 2014University of Edinburgh - Edinburgh, Scotland
Certifications
- Machine Learning SpecializationJULY 2017 - PRESENTCoursera
